Santiago Miret
Santiago Miret
AI Researcher
Verified email at - Homepage
Cited by
Cited by
Collaborative evolutionary reinforcement learning
S Khadka, S Majumdar, T Nassar, Z Dwiel, E Tumer, S Miret, Y Liu, ...
International conference on machine learning, 3341-3350, 2019
Evolutionary reinforcement learning for sample-efficient multiagent coordination
S Majumdar, S Khadka, S Miret, S McAleer, K Tumer
International Conference on Machine Learning, 6651-6660, 2020
Multi-objective gflownets
M Jain, SC Raparthy, A Hernández-Garcıa, J Rector-Brooks, Y Bengio, ...
International conference on machine learning, 14631-14653, 2023
Protst: Multi-modality learning of protein sequences and biomedical texts
M Xu, X Yuan, S Miret, J Tang
International Conference on Machine Learning, 38749-38767, 2023
Faenet: Frame averaging equivariant gnn for materials modeling
AA Duval, V Schmidt, A Hernández-Garcıa, S Miret, FD Malliaros, ...
International Conference on Machine Learning, 9013-9033, 2023
Group SELFIES: a robust fragment-based molecular string representation
AH Cheng, A Cai, S Miret, G Malkomes, M Phielipp, A Aspuru-Guzik
Digital Discovery 2 (3), 748-758, 2023
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems
A Duval, SV Mathis, CK Joshi, V Schmidt, S Miret, FD Malliaros, T Cohen, ...
arXiv preprint arXiv:2312.07511, 2023
Storage wars: Batteries vs. supercapacitors
S Miret
Berkeley Energy and Resources Collaborative, November 10, 2013
Matsci-nlp: Evaluating scientific language models on materials science language tasks using text-to-schema modeling
Y Song, S Miret, B Liu
arXiv preprint arXiv:2305.08264, 2023
Can retriever-augmented language models reason? the blame game between the retriever and the language model
P BehnamGhader, S Miret, S Reddy
arXiv preprint arXiv:2212.09146, 2022
Optimizing memory placement using evolutionary graph reinforcement learning
S Khadka, E Aflalo, M Marder, A Ben-David, S Miret, S Mannor, T Hazan, ...
arXiv preprint arXiv:2007.07298, 2020
Learning intrinsic symbolic rewards in reinforcement learning
HU Sheikh, S Khadka, S Miret, S Majumdar, M Phielipp
2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022
ChemOS 2.0: An orchestration architecture for chemical self-driving laboratories
M Sim, MG Vakili, F Strieth-Kalthoff, H Hao, RJ Hickman, S Miret, ...
Matter, 2023
The open MatSci ML toolkit: A flexible framework for machine learning in materials science
S Miret, KLK Lee, C Gonzales, M Nassar, M Spellings
arXiv preprint arXiv:2210.17484, 2022
Neuroevolution-enhanced multi-objective optimization for mixed-precision quantization
S Miret, VS Chua, M Marder, M Phiellip, N Jain, S Majumdar
Proceedings of the Genetic and Evolutionary Computation Conference, 1057-1065, 2022
Are LLMs Ready for Real-World Materials Discovery?
S Miret, NM Krishnan
arXiv preprint arXiv:2402.05200, 2024
PhAST: Physics-aware, scalable, and task-specific GNNs for accelerated catalyst design
A Duval, V Schmidt, S Miret, Y Bengio, A Hernández-García, D Rolnick
Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, and Matthew Spellings. The open matsci ml toolkit: A flexible framework for machine learning in materials science
S Miret
arXiv preprint arXiv:2210.17484, 2022
Towards equilibrium molecular conformation generation with GFlowNets
A Volokhova, M Koziarski, A Hernández-García, CH Liu, S Miret, P Lemos, ...
Digital Discovery 3 (5), 1038-1047, 2024
EGraFFBench: evaluation of equivariant graph neural network force fields for atomistic simulations
V Bihani, S Mannan, U Pratiush, T Du, Z Chen, S Miret, M Micoulaut, ...
Digital Discovery 3 (4), 759-768, 2024
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